Chef League challenges you to improvise recipes like the pros

Beth Altringer‘s Chef Leaguemobile game on iOS is sure to make your mouth water. It is a game that challenges players to come up with the right ingredients to make a particular problem dish taste better. You can take up challenges and compete with other human players. To spice up a dull dish, you have to select an ingredient to make it better. The game’s artificial intelligence engine will determine who gets the right answer, and the winner gets to take the ingredients of the two other losers.

“It’s a multiplayer simulation game, where we’re simulating chef skills,” Altringer said in an interview with GamesBeat. “It occurred to me that my research was in effect building a backend for a simulation game that you could learn from.”

It’s a free-to-play game, but you have to acquire ingredients, either through play or by purchasing them. If you guess correctly that a burger with too much mayo could use something acidic or crunchy. Something acidic would change the taste of the mayonnaise, while something crunchy will distract you from it. If you come up with a better answer than your rival, you win.

The genesis of Chef League

Above: Beth Altringer is a Harvard professor by day with a side job of creating Chef League.

It reminded me of the genesis of Glu Mobile’s games, Covet Fashion and Design Home, made by its CrowdStar division, with different audiences in mind. Altringer was inspired in part while playing Design Home, which lets you design home interiors that are then voted on by other players. The games have big female audiences, and they’re designed for new kinds of players.

Altringer is a Harvard engineering professor by day. But she played Design Home and found it fun and relaxing. But she hoped that she could make something herself that could teach people something about one of her favorite hobbies. She was deep into advanced flavor analytics.

“I happen to be really into food and I am a big nerd,” she said. “I have been studying how humans taste perception as flavor and how chefs learn to improvise. It’s not like there is a standard chef training. All of them acquire literacy in flavor, but they do it in different ways. I built software that would allow you to navigate flavor like an expert, even if you’re a novice.”

Above: Chef League challenges you to fix a dish with better flavor.

A lot of other cooking games are on mobile devices, including Diner Dash and Glu’s Gordon Ramsay Dash. But a lot of those are about time management rather than learning about cooking.

“They are about chef skills, but not about flavor,” Altringer said. “I wanted something different and wasn’t able to find it somewhere else.”

And Chef League has the science of flavor analytics behind it. It gamifies learning for understanding why people like certain kinds of foods. It also features photorealistic food imagery, while other games are animated. It features multiplayer competition inspired by cooking shows, and it has bite-sized game sessions. It is targeted for both gamers and non-gamers alike.

Above: Chef League’s opening screen

Altringer worked on it for three years. Chef League features a set of “AI Chefs” that live inside the game. These chefs represent common preference patterns derived from scientific flavor data and 1.5 million natural language reviews of real recipes.

They function like automated reality TV chef judges, each ‘voting’ according to historical palate preferences. They exist to help players casually learn. You have a pantry of items you own and a shop where you can buy new items. The AI chef coach gives you real feedback. If the winner isn’t clear, it goes to social voting.

“Our automated judging is based on historical data, but there are other things people love that experts wouldn’t necessarily advocate,” Altringer said.

Doing food research

Above: Beth Altringer (tallest), Tracy Chang, and her friends.

During graduate school, Altringer trained with the Cambridge University Blind Wine Tasting Society and went on to compete internationally, winning the competition hosted by Bollinger Champagne House in France.

In 2015, she began quantifying flavor more broadly, creating the Flavor Genome Project (FGP) to study patterns in food flavor perception. The project integrated scientific flavor data, analysis of real recipe reviews, and research on how chefs and sommeliers learn.

She learned, for instance, why french fries go well with ketchup.

“French fries are a predominantly fatty taste,” she said. “It’s the fattiness that people are after. And if something is too fatty, then cutting it with acidity improves the perceived balance. Tomatoes are highly acidic. And ketchup is also sweet, but it is also a lot more acidic than people probably realize. And that combination is really nice.”

In 2017, Altringer took that research and started creating a game that could teach amateur cooks about the ways that chefs think about flavor. That, in turn, might help people make healthier, more flavorful choices in preparing their own food. Altringer recently held a party with Boston chef Tracy Chang, who helped her as a friend on how chefs think.

Making it fun

Above: Chef League’s recent party

“Flavor data exists in a lot of places, from cookbooks to flavor media TV shows, to online recipes,” Altringer said. “When we consume that data, you learn to copy the recipe. But you don’t learn what makes that recipe taste so good compared to a different recipe. I think a natural future for food media includes games, and this is an attempt at that.”

Altringer tried to make sure that the game wasn’t too hard. She didn’t want you to be an expert to just be able to play the game. And she didn’t want to make it so you put bacon on everything in order to win.

“Our automated judging is based on historical data, but there are other things people love that experts wouldn’t necessarily advocate,” Altringer said.

Above: Chef League’s challenges

Altringer, who has a master’s degree in architecture, was trained as a designer. She created almost all of it herself. Now she wants to find others to work with to help craft it into a better game so that she can do updates. She has some helpers now and is looking for more.

The game does not have a ton of players yet, but the average play sessions are 30 minutes to an hour, and the average number of sessions per day is 3.5.

“Our goal is to make sure that this will be something that a lot of people will enjoy playing as a relaxing game,” Altringer said. “We will learn fast and improve it.”

MAY 2019

A New App is Transforming Learning Through AI

How gamified AI is being used to teach us about our own tastes.

When we think of artificial intelligence or machine learning, we often think of a robot or algorithm automating a repetitive task that is menial for humans. One of my favorite examples is object detection: identifying pre-trained classes of objects (like people or cars) within an image or video. This application of AI is often seen as competing with human beings; AI which can detect mistakes in manufactured goods can replace the worker who used to perform quality control.

AI as Human Augmenting

Of course there are other applications of AI that augment human experience directly, in ways that were impossible before. The algorithm behind Spotify’s Discover Weekly playlist is one example: the algorithm exposes you to music you’d otherwise never have listened to, enriching your experience and curating your music tastes.

And now there’s an app that’s breaking new ground by using AI to improve human skill, in a domain most of us could use a little help with: cooking.

Chef League, which jusT launched on the app store, teaches users to cook better by pitting them against AI chefs as they attempt to choose the best ingredient to fix a bad recipe — specifically a recipe scraped from the internet with one star reviews.

As in most successful artificial intelligence implementations, the AI chefs in the Chef League app rely on vast amounts of data, in this case millions of online recipe reviews. The engineers behind the app used natural language processing, sentiment analysis, and clustering algorithms in order to develop eight distinct personas that describe the most common flavor palates.

When I reached out to the app’s founder, Harvard Engineering Professor Beth Altringer, she described the process of building the AI chef personas, comparing it to the strategy behind Spotify’s Discover Weekly: “It took me three years to build the dataset through the Flavor Genome Project, and get to the point of identifying distinctive and predictive reviewer palates. What I mean by this is similar to how a company like The Echo Nest was able to use real review data matched up to song data to identify new ‘genres’ that were entirely data-driven. We have been doing something similar by matching review data to recipes and discovering data-driven palates. Eventually, a subset of these became the AI Chef Coaches that live inside of the Chef League game.” (The Echo Nest is the company Spotify bought to power their Discover Weekly Algorithm.)

Cooking Up a New Way to Learn

Notice how in both Spotify and Chef League, artificial intelligence doesn’t replace human understanding, but rather enables humans to learn in a way that was impossible before. When we think about the way food tastes — the flavors we enjoy, or the unpleasant ones (too salty, too bitter) — we often think of it as a highly subjective experience. However, by processing and clustering the subjective preferences encoded in millions of recipe reviews, Chef League is able to produce new insights (in the form of AI chefs) which would have been impossible for humans to generate on their own. Even if you sat down and read through millions of reviews, there would be no way for you to summarize or use that information in a compelling way. AI has unlocked this information and made it possible to improve in our all too human task of making a tasty meal.

Altringer firmly believes that there is huge potential in applying AI to education, particularly in fields where we may struggle to adequately describe our experience: “I draw a lot of inspiration from what Spotify and Pandora both did, in different ways, for music. They let users find music they love even if they lack the expert vocabulary to find it. You can find something you’ll enjoy via their algorithms even if you don’t know the artist’s name, the song name, the beats per minute, the mood, the album name, the genre, etc. I love that.”

Chef League differs from Spotify and Pandora, however, in that it will actually help users understand their own food tastes better in a way Spotify and Pandora have yet to do explicitly, as Altringer writes, “I wish there were an educational layer to what they built that also helped me understand my music tastes better. Flavor has a similar challenge. People consume the same things over and over, not because they lack a sense of adventure, but because they are limited by the language they know for searching for flavor experiences.”

A screenshot provided by Altringer

The Brighter Future of AI

While AI’s economic disruption deserves a healthy skepticism — manual tasks will continue to be automated while new jobs will be created — AI’s ability to unlock previously unattainable insights and augment human potential is incredibly exciting. Even with Chef League, Altringer already has plans to iterate on the app using more data: for example, using food waste data in order to encourage users to become more efficient cooks.

It’s easy to see how this sort of AI training might be applied across other disciplines as well: perhaps a fitness app could determine whether you should focus more on cardio or strength building (of course, it’s probably cardio), or a spending app like Mint could train you how to better manage your finances. Ultimately, though, it will depend first on a pleasant user experience. Talking about her goals for the app, Altringer wrote: “What I hope to do with Chef League is first and foremost to simply make it fun. If that fails, the whole thing fails. If that succeeds, there is so much more a game like this can do.” While Chef League is a first step, it offers a window into a future where gamified AI teaches us more than we ever knew about ourselves.

Harvard faculty member develops game to teach people about food and flavor

Standing over a steaming pot that holds the evening’s dinner, you scoop out a spoonful to taste the delicious fruits of your labor and find the dish to be completely blasé, as if it is missing some key ingredient. With a pantry teeming with different spices and a fully stocked fridge, what ingredient do you reach for that could rescue this dish from mediocrity?

The game pits users against other humans and digital chefs in heated competitions to fix bad recipes.

“I admire people who, faced with a kitchen of empty cabinets, can whip up a masterpiece – like Samin Nosrat describes so well in ‘Salt, Fat, Acid, Heat.’ I built this game to teach myself how chefs improvise and fix recipe problems intuitively,” said Altringer, Director of the Desirability Lab and Senior Preceptor in Innovation and Design. “The goal is to provide a platform for all of us to learn by gaming.”

The game includes several types of challenges. In a recipe challenge, the player is presented with a bad recipe—a ‘one-star’ recipe scraped from cooking websites—and goes up against two chefs in a competition to make the biggest improvement to the dish.

For instance, one challenge serves up a dull margherita pizza that needs to taste fresher or spicier. A player searches through a database of ingredients, which provides information about the flavors of each, and chooses one item to add. The winner selects the ingredient that most improves the taste of the dish, based on ratings from culinary experts.

The game includes several digital competitors—artificial intelligence chefs that were built by conducting natural language processing on the text of millions of online recipe reviews. Altringer utilized sentiment scores and topic modeling to create eight data-driven chef personas. While flavor is subjective, the AI chefs are designed to represent the most common palates.

In addition to repairing recipes, Chef League helps human players improve their palates. Users are asked to rate the sweetness, sourness, richness, spiciness, crunchiness, and savoriness of different ingredients on a sliding scale, and then compare their answers to those of culinary experts.

“A lot of people have never actually stopped and thought about how these different ingredients actually taste,” Altringer said. “This could open up someone’s eyes to new flavors. Blueberries, for example, are not only sweet; they are also more acidic than tomatoes. If you learn this, you might try blueberries the next time you need to brighten up flavors with acidity.”

Altringer’s interest in food and flavor began during her days as a graduate student at the University of Cambridge, where she participated in international blind wine tasting competitions. She was fascinated by the ability to tell the story of how a wine is made by tasting it, zeroing in on everything from the drink’s chemical properties to the type of soil where the grapes were grown.

At Harvard, Altringer leveraged that interest into the Flavor Genome Project, an online database that enables users to look up any ingredient and see its flavor attributes. In addition to listing details like acidity level, the database also describes foods it pairs well with and commonly confused ingredients.

When the database proved to be too complex for a casual cook, Altringer used it to build a mobile game to teach amateurs.

“The casual, mobile game space is clearly very engaging, but there is room for fun-first games that are also teaching you something for your offline life,” she said. “I would love for this to eventually become a platform for interactive understanding about food and flavor.”

She hopes to continue adding new elements to Chef League. Altringer would like to incorporate sponsored ingredients, perhaps in partnership with the U.N. World Food Program’s food waste initiative, for instance, where a user could earn extra points for using an ‘ugly’ carrot that might typically be discarded.

Altringer would also like to get chefs in the game. Chef League currently incorporates data from chefs, but she hopes to have human chefs compete, providing inspiration and advice to users. Future versions may also include the latest science about flavor compounds and the genetics of a person’s taste preferences to give casual users access to state-of-the-art knowledge.

“You can read a chef’s memoir or a cookbook, make every recipe from a culinary website, but you still haven’t learned to be creative in your own way,” she said. “You haven’t developed your own chef intuition in a way that capacitates you to do more. Why can’t these different touch points build on each other to teach how flavors work?”

MARCH 2019

Chef League Launches for Pre-order on the App Store

CHEF LEAGUE – New Game Helps You Improvise Recipes Like Pro Chefs Launches for Pre-Order at SXS

Now available on the App Store for Pre-Order is the world’s first research-based game proven to teach you how to think more like an expert chef and make healthier, flavorful choices. The game was created by Dr. Beth Altringer (Harvard engineering and MSMBA program faculty, and former champion taster) with machine learning to help people learn to improvise delicious, healthy recipes. Think Duolingo or Rosetta Stone meets Guitar Hero… for learning what expert chefs know.

CHEF LEAGUE stands out from existing food media and games with these unique features:

Science-quality flavor analytics gamified for learning, when similar quality analytics are not gamified and usually only used to power major website recipe search

High-end food media graphics, when other games are animated

Multi-player competition inspired by reality TV cooking shows, which is new

Bite-sized gameplay sessions

Intended for gamers and non-gamers alike

After three years of bootstrapped development, Beth Altringer launched Chef League for Pre-Order on International Women’s Day during the SXSW Festival in Austin. Chef League features a set of “AI Chefs” that live inside the game. These chefs represent common preference patterns derived from scientific flavor data and 1.5 million natural language reviews of real recipes. They function like automated reality TV chef judges, each ‘voting’ according to historical palate preferences. They exist to help players casually learn. Prior to its public launch, Chef League is focused on building community and forming partnerships. Burak Cakmak, Dean at Parsons School of Design, recently joined the advisory board.

Background the Founder of Chef League

During graduate school, Altringer trained with the Cambridge University Blind Wine Tasting Society and went on to compete internationally, winning the competition hosted by Bollinger Champagne House in France. In 2015, she began quantifying flavor more broadly, creating the Flavor Genome Project (FGP) to study patterns in food flavor perception. The project integrated scientific flavor data, analysis of real recipe reviews, and research on how chefs and sommeliers learn. In 2017, she had the idea to turn FGP’s research into what would become Chef League.

“I admire people who, faced with an empty kitchen pantry, can whip up a masterpiece. I built this game initially to teach myself how chefs improvise and fix recipe problems on the fly. My larger goal is to provide a platform for other people to learn from experts by gaming.” – Beth Altringer, Chef League

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